Article
Chemistry, Physical
Jeremy P. Coe
Summary: We develop analytic gradients for selected configuration interaction wave functions, showing that degenerate orbital pairs belonging to different irreducible representations in the largest abelian subgroup do not need to be included and instabilities due to degeneracies are avoided. We introduce seminumerical gradients and use them to validate the analytic approach even when near degeneracies are present. The method is applied to various molecules, demonstrating the high-quality and efficiency of the analytic gradients for selected configuration interaction.
JOURNAL OF CHEMICAL THEORY AND COMPUTATION
(2023)
Article
Chemistry, Physical
J. Villalobos-Castro, Iryna Knysh, Denis Jacquemin, Ivan Duchemin, Xavier Blase
Summary: We propose a method for calculating excited-state analytic gradients in the Bethe-Salpeter equation formalism. The method uses an adapted Lagrangian Z-vector approach to achieve a cost independent of the number of perturbations. We evaluate the accuracy of common approximations in the Bethe-Salpeter community and compare the results with time-dependent density-functional theory (TD-DFT) data.
JOURNAL OF CHEMICAL PHYSICS
(2023)
Article
Chemistry, Physical
Daniel Gibney, Jan-Niklas Boyn, David A. Mazziotti
Summary: Researchers demonstrate how to transform DFT into a one-electron reduced-density-matrix (1-RDM) functional theory to address the limitations of accurately describing the electronic structure of strongly correlated systems. This method retains favorable computational scaling compared to traditional DFT and achieves substantial improvements in the description of static correlation in chemical structures and processes.
JOURNAL OF PHYSICAL CHEMISTRY LETTERS
(2022)
Article
Chemistry, Physical
Hiroya Nakata, Dmitri G. Fedorov
Summary: The analytic energy gradient of energy with respect to nuclear coordinates is derived for the fragment molecular orbital (FMO) method combined with time-dependent density functional theory (TDDFT). The response terms arising from the use of a polarizable embedding are derived. The obtained analytic FMOTDDFT gradient is shown to be accurate in comparison to both numerical FMO-TDDFT and unfragmented TDDFT gradients, at the level of two-and three-body expansions. The gradients are used for geometry optimizations, molecular dynamics, vibrational calculations, and simulations of IR and Raman spectra of excited states. The developed method is used to optimize the geometry of the ground and excited electronic states of the photoactive yellow protein (PDB: 2PHY).
JOURNAL OF CHEMICAL THEORY AND COMPUTATION
(2023)
Article
Chemistry, Physical
Yoshio Nishimoto
Summary: In multi-reference perturbation theory, the computational cost of analytic derivatives is strongly influenced by the size of the active space used in the reference self-consistent field calculation. By developing and implementing analytic gradients for restricted active space second-order perturbation theory (RASPT2) and complete active space second-order perturbation theory (CASPT2), previous limitations on active space size have been overcome, allowing for geometry optimizations with larger active spaces.
JOURNAL OF CHEMICAL PHYSICS
(2021)
Article
Chemistry, Physical
Edward G. Hohenstein, Oumarou Oumarou, Rachael Al-Saadon, Gian-Luca R. Anselmetti, Maximilian Scheurer, Christian Gogolin, Robert M. Parrish
Summary: We propose a Lagrangian-based approach to evaluate relaxed one- and two-particle reduced density matrices from double factorized Hamiltonians, which improves efficiency in computing nuclear gradient and derivative properties.
JOURNAL OF CHEMICAL PHYSICS
(2023)
Article
Chemistry, Physical
Chenchen Song, Jeffrey B. Neaton, Todd J. Martinez
Summary: A new method for CASPT2 analytical gradients is proposed in this study, utilizing the supporting subspace method and MP2, Fock derivatives, which can calculate gradients more efficiently, reduce computational costs, and has wide applications in fields such as ab initio molecular dynamics simulations and geometry optimization.
JOURNAL OF CHEMICAL PHYSICS
(2021)
Article
Physics, Multidisciplinary
Eli Chertkov, Benjamin Villalonga, Bryan K. Clark
Summary: The study shows the existence of many-body localization phenomena in quantum systems in higher dimensions, and an algorithm has been developed to search for approximate binary l bits. The algorithm successfully identified high-quality l bits in different models, and observed rapid changes in the distribution of l bits at specific disorder strengths, suggesting the presence of MBL transitions.
PHYSICAL REVIEW LETTERS
(2021)
Article
Chemistry, Physical
Huanchen Zhai, Garnet Kin-Lic Chan
Summary: Recent interest in deploying ab initio density matrix renormalization group (DMRG) computations on high performance computing platforms has led to a reformulation of the conventional distributed memory ab initio DMRG algorithm. Various parallelism strategies are explored to reduce processor load imbalance and communication cost for achieving higher efficiencies. The performance of the new open-source implementation is demonstrated with benchmark calculations on benzene and FeMo cofactor models, showing nearly ideal parallel scaling from 448 to 2800 CPU cores.
JOURNAL OF CHEMICAL PHYSICS
(2021)
Article
Chemistry, Physical
Tom Reichert, Marija Vucicevic, Paula Hillman, Marcus Bleicher, Sanja J. Armakovic, Stevan Armakovic
Summary: This study used DFT and SAPT calculations, along with MD simulations, to investigate the interaction between a sumanene molecule and 5-fluorouracil (5-FU). The results showed that 5-FU binds more strongly to the concave side of sumanene. Different geometric shapes of sumanene also influenced the interaction between sumanene and 5-FU.
JOURNAL OF MOLECULAR LIQUIDS
(2021)
Article
Chemistry, Physical
Daniel Gibney, Jan-Niklas Boyn, David A. Mazziotti
Summary: Researchers combine 1-RDMFT method with different DFT functionals and Hartree-Fock method to address the issue of describing systems with statically correlated electrons. They also generalize the information density matrix functional theory (iDMFT) as a correction to the Hartree-Fock method by incorporating density functionals, and benchmark it with the 1-RDMFT method.
JOURNAL OF CHEMICAL THEORY AND COMPUTATION
(2022)
Article
Green & Sustainable Science & Technology
Haoming Liu, Shuxian Deng, Salman Habib, Bo Shen
Summary: With the increasing demand for refrigeration, the electricity consumed in the refrigeration field is also growing, leading to environmental challenges. This study examines emission reduction-oriented configuration schemes in the refrigeration field using Ningbo, China as a case study. The research shows that proper configuration of distributed photovoltaic and energy storage devices can effectively reduce costs and emissions in the refrigeration field.
JOURNAL OF CLEANER PRODUCTION
(2022)
Article
Chemistry, Physical
Elisa Rebolini, Marie-Bernadette Lepetit
Summary: In this paper, a novel and efficient parallel implementation, RelaxSE, is presented for calculating the low-lying excited states and energies of strongly correlated systems. This method, based on the Selected Active Space + Single excitations, is designed to tackle systems with numerous open shells per atom. Evaluation on a test set shows linear scaling with respect to the number of determinants and a small overhead due to parallelization.
JOURNAL OF CHEMICAL PHYSICS
(2021)
Article
Chemistry, Physical
Jozsef Csoka, Mihaly Kallay
Summary: We present analytic gradients for local density fitting Hartree-Fock (HF) and hybrid Kohn-Sham (KS) density functional methods. Due to the non-variational nature of the local fitting algorithm, the method of Lagrange multipliers is used to avoid the solution of the coupled perturbed HF and KS equations. Efficient algorithms for Z-vector equations and gradient calculation are proposed, preserving the scalability and low memory requirement of the original local fitting algorithm.
JOURNAL OF CHEMICAL PHYSICS
(2023)
Article
Engineering, Electrical & Electronic
Kuangang Fan, Haonan Hou, Yaofeng Tang, Pingchuan Liu
Summary: This paper explores a new method, OC-ACMA, which incorporates statistical signal orthogonality into ACMA for improved signal separation and recovery. Results show that OC-ACMA can successfully separate and recover constant modulus signals at higher accuracy.